On-chip hybrid power supply system for wireless sensor nodes

ACM Journal on Emerging Technologies in Computing Systems, 2014.

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structuresmicroprogrammingcontrolreconfiguration
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We proposed the schematic of fuel cell based onchip FC-Bat hybrid power system which consists of on-chip fuel cells served as the primary source and on-chip rechargeable battery served as the secondary source

Abstract:

With the miniaturization of electronic devices, small size but high capacity power supply system appears to be more and more important. A hybrid power source, which consists of a fuel cell (FC) and a rechargeable battery, has the advantages of long lifetime and good load following capabilities. In this paper, we propose the schematic of a...More

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Introduction
  • Wireless sensor networks have gained increasing popularity.For example, wireless sensor networks have a great impact on environment monitoring, data collecting, danger warning etc.
  • In order to maximize the lifetime of power system, several energy self-supply systems have been proposed [7]
  • These systems could supply themselves depending on converting other energy, such as solar energy, motional energy, or chemical energy etc, to electronic energy automatically.
  • These self-supply systems are not controllable, and influenced by the environment greatly
  • They are not good choices for the embedded system which needs power supply continuously.
  • An external power supply system must be utilized to keep the embedded system work properly
Highlights
  • In recent years, wireless sensor networks have gained increasing popularity.For example, wireless sensor networks have a great impact on environment monitoring, data collecting, danger warning etc
  • Our contributions includes: 1) We explore the possibility of an on-chip fuel cell based hybrid power system for embedded systems, especially for the wireless sensor nodes design
  • A typical wireless sensor node applied in low duty cycle is utilized in our work, which mainly consists of Micaz and MTS310 [25], and has a 7.3728MHZ working frequency, 250 kbps transferring rate
  • We proposed the schematic of fuel cell based onchip FC-Bat hybrid power system which consists of on-chip fuel cells served as the primary source and on-chip rechargeable battery served as the secondary source
  • We proposed an power control method based on traditional dynamic power management for on-chip FC-Bat hybrid power system used in wireless sensor nodes (WSN)
  • Taking the wireless sensor node powered by this hybrid power system as an example, the simulation results demonstrated that compared with wafer-level battery, FC-Bat hybrid power system can achieve about 16% energy saving
Results
  • A typical wireless sensor node applied in low duty cycle is utilized in the work, which mainly consists of Micaz and MTS310 [25], and has a 7.3728MHZ working frequency, 250 kbps transferring rate.
  • Light and Temperature information, are acquired in each cycle.
  • In Figure 8, the current consumption within one working cycle is presented and scaling to onchip integrated conditions.
  • From the point of minimized energy consumption, the authors will evaluate how the hybrid power system behaves and find out the most efficient operating pattern.
  • Operation mode Io−a Io−i Battery.
  • SIMULATION RESULTS OF TWO EXTREME OPERATION STATES.
  • Operation state Active time Cycle time Hybrid EC Battery only EC
Conclusion
  • The authors proposed the schematic of fuel cell based onchip FC-Bat hybrid power system which consists of on-chip fuel cells served as the primary source and on-chip rechargeable battery served as the secondary source.
  • For one on-chip power system with 1cm2 area, the wafer-level battery can power a typical sensor node for only about 5 months, while the on-chip hybrid power system can supply the same sensor node for over 2 years steadily
Summary
  • Introduction:

    Wireless sensor networks have gained increasing popularity.For example, wireless sensor networks have a great impact on environment monitoring, data collecting, danger warning etc.
  • In order to maximize the lifetime of power system, several energy self-supply systems have been proposed [7]
  • These systems could supply themselves depending on converting other energy, such as solar energy, motional energy, or chemical energy etc, to electronic energy automatically.
  • These self-supply systems are not controllable, and influenced by the environment greatly
  • They are not good choices for the embedded system which needs power supply continuously.
  • An external power supply system must be utilized to keep the embedded system work properly
  • Objectives:

    The authors begin with some definitions used in this algorithm as shown in Table II. The authors' goal is to minimize the fuel consumption for each task.
  • Results:

    A typical wireless sensor node applied in low duty cycle is utilized in the work, which mainly consists of Micaz and MTS310 [25], and has a 7.3728MHZ working frequency, 250 kbps transferring rate.
  • Light and Temperature information, are acquired in each cycle.
  • In Figure 8, the current consumption within one working cycle is presented and scaling to onchip integrated conditions.
  • From the point of minimized energy consumption, the authors will evaluate how the hybrid power system behaves and find out the most efficient operating pattern.
  • Operation mode Io−a Io−i Battery.
  • SIMULATION RESULTS OF TWO EXTREME OPERATION STATES.
  • Operation state Active time Cycle time Hybrid EC Battery only EC
  • Conclusion:

    The authors proposed the schematic of fuel cell based onchip FC-Bat hybrid power system which consists of on-chip fuel cells served as the primary source and on-chip rechargeable battery served as the secondary source.
  • For one on-chip power system with 1cm2 area, the wafer-level battery can power a typical sensor node for only about 5 months, while the on-chip hybrid power system can supply the same sensor node for over 2 years steadily
Tables
  • Table1: PARAMETERS USED IN OUR FC MODELING. E (V) A In (A) R (Ω) m n
  • Table2: SIMULATION RESULTS IN ONE WHOLE TASK OR FIVE SUB-TASKS.Io−a
  • Table3: DEFINITIONS IN OUR DYNAMIC POWER MANAGEMENT ALGORITHM FOR
  • Table4: ENERGY CONSUMPTION (EC) OF FIVE WORKING PATTERNS (mJ )
  • Table5: SIMULATION RESULTS OF TWO EXTREME OPERATION STATES. TIME IN s,
  • Table6: COMPARISON OF TWO KINDS OF POWER SOURCES. EC: ENERGY
Download tables as Excel
Related work
  • A. Hybrid Power Systems

    Many hybrid power system structures have been proposed. In general, they can be divided into four categories depending on their components: fuel cell-battery hybrid power system [4]–[6], fuel cellsupercapacitor hybrid power system [8]–[13], battery- supercapacitor hybrid power system [14]–[16], and fuel cell-supercapacitor-battery hybrid power system [17]–[19]. Fuel cell-battery hybrid power system combining the characteristics of fuel cell’s high energy density and battery’s good load current following ability has been widely used in some portable devices, such as camcorders. With the characteristics of fuel cell’s high energy density, supercapacitor’s high capacity and quick charging or discharging ability, but no transitory step current provided, fuel cell-supercapacitor hybrid power system is always utilized to power some high power devices, such as the vehicles. For battery-supercapacitor hybrid power system, which has relative low energy density comparing with fuel cell-supercapacitor hybrid power system, is always utilized as energy storage system for wind applications or power supply system for some vehicles. Fuel cellbattery -supercapacitor hybrid power system has high energy density, long cycle life, good load current following ability, and etc. However, these advantages are achieved at the cost of large area. In summary, supplying power for some low power devices, especially on-chip devices, such as micro sensor node, fuel cell-battery hybrid power system is the best choice.
Funding
  • 1This work was supported in part by National Science and Technology Major Project, 2010ZX01030-001-001-04, NSFC (60870001), by 863 Program of China (2009AA01Z130), and by TNlist Cross-discipline Foundation
  • Yuan Xie’s work was supported in part by grants from NSF 0643902, 0702617, and a SRC grant
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